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Amirhossein Kiani of Bina Technologies gave a talk at Hack Reactor on why the world of genomics needs as many coders as it can find. The hour-long session went into the past and future of genetic research, some of the many applications of genomics, and even included a crash course in the workings of DNA.

After showing a brief video on a woman who defeated stage IV lung cancer with the help of genomic sequencing, Kiani presented these startling facts: it took 13 years and $3 billion to sequence the first human genome. Today it takes 24 hours and $1,000. These metrics will only continue to improve with research.

“It’s only going to get cheaper. It’s only going to get faster,” said Kiani.

Because genetic data can be turned into binary data, some of the major goals of genomics are now in the realm of Software Engineers.

“There needs to be a platform, software and hardware for this,” Kiani explains. “If you’re experienced in software, you could really move this forward and have a lot of impact.”

You can watch Kiani’s entire presentation below.

The real-world applications of genomics are startling, and growing every day. While many people have heard of the ability to find out about a propensity for a certain disease, there are many other uses. One can test for various mutations that are likely to be passed on to offspring and even examine a fetus’ genetic code by extracting its blood cells from that of the mother.

The field of personalized medicine is also growing, and unique treatments can be charted by examining a person’s genetic code.

“You can draw blood and detect that there will be a tumor, and detect cancer very early on,” Kiani notes.

Analyzing DNA is “like anything else,” Kiani describes. “We have an analog signal, and we turn it into digital.” This is done, by putting DNA through a sequencer, which reads the genetic code and turns it into ones and zeroes.

Near the end of his talk, Kiani gave a pitch for Software Engineers entering the world of genomics:

“As Software Engineers, we do automation really well. We come up with elegant solutions for complex problems. We can build things that work at scale. We can optimize and identify bottlenecks. We build production grade code. Genetic research needed these things yesterday. You can make the world a better place by taking your skillset from software to genomics.”

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